This disclosure relates to efficiently controlling and/or scheduling the operation of an energy-consuming system, such as a heating, ventilation, and/or air conditioning (HVAC) system by encouraging energy-efficient user feedback.
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present techniques, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
While substantial effort and attention continues toward the development of newer and more sustainable energy supplies, the conservation of energy by increased energy efficiency remains crucial to the world's energy future. According to an October 2010 report from the U.S. Department of Energy, heating and cooling account for 56% of the energy use in a typical U.S. home, making it the largest energy expense for most homes. Along with improvements in the physical plant associated with home heating and cooling (e.g., improved insulation, higher efficiency furnaces), substantial increases in energy efficiency can be achieved by better control and regulation of home heating and cooling equipment. By activating heating, ventilation, and air conditioning (HVAC) equipment for judiciously selected time intervals and carefully chosen operating levels, substantial energy can be saved while at the same time keeping the living space suitably comfortable for its occupants.
Historically, however, most known HVAC thermostatic control systems have tended to fall into one of two opposing categories, neither of which is believed be optimal in most practical home environments. In a first category are many simple, non-programmable home thermostats, each typically consisting of a single mechanical or electrical dial for setting a desired temperature and a single HEAT-FAN-OFF-AC switch. While being easy to use for even the most unsophisticated occupant, any energy-saving control activity, such as adjusting the nighttime temperature or turning off all heating/cooling just before departing the home, must be performed manually by the user. As such, substantial energy-saving opportunities are often missed for all but the most vigilant users. Moreover, more advanced energy-saving capabilities are not provided, such as the ability for the thermostat to be programmed for less energy-intensive temperature setpoints (“setback temperatures”) during planned intervals of non-occupancy, and for more comfortable temperature setpoints during planned intervals of occupancy.
In a second category, on the other hand, are many programmable thermostats, which have become more prevalent in recent years in view of Energy Star (US) and TCO (Europe) standards, and which have progressed considerably in the number of different settings for an HVAC system that can be individually manipulated. Unfortunately, however, users are often intimidated by a dizzying array of switches and controls laid out in various configurations on the face of the thermostat or behind a panel door on the thermostat, and seldom adjust the manufacturer defaults to optimize their own energy usage. Thus, even though the installed programmable thermostats in a large number of homes are technologically capable of operating the HVAC equipment with energy-saving profiles, it is often the case that only the one-size-fits-all manufacturer default profiles are ever implemented in a large number of homes. Indeed, in an unfortunately large number of cases, a home user may permanently operate the unit in a “temporary” or “hold” mode, manually manipulating the displayed set temperature as if the unit were a simple, non-programmable thermostat.
Proposals have been made for so-called self-programming thermostats, including a proposal for establishing learned setpoints based on patterns of recent manual user setpoint entries as discussed in US20080191045A1, and including a proposal for automatic computation of a setback schedule based on sensed occupancy patterns in the home as discussed in G. Gao and K. Whitehouse, “The Self-Programming Thermostat: Optimizing Setback Schedules Based on Home Occupancy Patterns,” Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pp. 67-72, Association for Computing Machinery (November 2009). It has been found, however, that crucial and substantial issues arise when it comes to the practical integration of self-programming behaviors into mainstream residential and/or business use, issues that appear unaddressed and unresolved in such self-programming thermostat proposals. By way of example, just as there are many users who are intimidated by dizzying arrays of controls on user-programmable thermostats, there are also many users who would be equally uncomfortable with a thermostat that fails to give the user a sense of control and self-determination over their own comfort, or that otherwise fails to give confidence to the user that their wishes are indeed being properly accepted and carried out at the proper times. At a more general level, because of the fact that human beings must inevitably be involved, there is a tension that arises between (i) the amount of energy-saving sophistication that can be offered by an HVAC control system, and (ii) the extent to which that energy-saving sophistication can be put to practical, everyday use in a large number of homes. Similar issues arise in the context of multi-unit apartment buildings, hotels, retail stores, office buildings, industrial buildings, and more generally any living space or work space having one or more HVAC systems. It has been found that the user interface of a thermostat, which so often seems to be an afterthought in known commercially available products, represents a crucial link in the successful integration of self-programming thermostats into widespread residential and business use, and that even subtle visual and tactile cues can make a large difference in whether those efforts are successful.
Thus, it would be desirable to provide a thermostat having an improved user interface that is simple, intuitive, elegant, and easy to use such that the typical user is able to access many of the energy-saving and comfort-maintaining features, while at the same time not being overwhelmed by the choices presented. It would be further desirable to provide a user interface for a self-programming or learning thermostat that provides a user setup and learning instantiation process that is relatively fast and easy to complete, while at the same time inspiring confidence in the user that their setpoint wishes will be properly respected. It would be still further desirable to provide a user interface for a self-programming or learning thermostat that provides convenient access to the results of the learning algorithms and methods for fast, intuitive alteration of scheduled setpoints including learned setpoints. It would be even further desirable to provide a user interface for a self-programming or learning thermostat that provides insightful feedback and encouragement regarding energy saving behaviors, performance, and/or results associated with the operation of the thermostat. Notably, although one or more of the embodiments described infra is particularly advantageous when incorporated with a self-programming or learning thermostat, it is to be appreciated that their incorporation into non-learning thermostats can be advantageous as well and is within the scope of the present teachings. Other issues arise as would be apparent to one skilled in the art upon reading the present disclosure.
Indeed, consider that users can use a variety of devices to control home operations. For example, thermostats can be used to control home temperatures, refrigerators can be used to control refrigerating temperatures, and light switches can be used to control light power states and intensities. Extreme operation of the devices can frequently lead to immediate user satisfaction. For example, users can enjoy bright lights, warm temperatures in the winter, and very cold refrigerator temperatures. Unfortunately, the extreme operation can result in deleterious costs. Excess energy can be used, which can contribute to harmful environmental consequences. Further, device parts' (e.g., light bulbs' or fluids') life cycles can be shortened, which can result in excess waste.
Typically, these costs are ultimately shouldered by users. Users may experience high electricity bills or may need to purchase parts frequently. Unfortunately, these user-shouldered costs are often time-separated from the behaviors that led to them. Further, the costs are often not tied to particular behaviors, but rather to a group of behaviors over a time span. Thus, users may not fully appreciate which particular behaviors most contributed to the costs. Further, unless users have experimented with different behavior patterns, they may be unaware of the extent to which their behavior can influence the experienced costs. Therefore, users can continue to obliviously operate devices irresponsibly, thereby imposing higher costs on themselves and on the environment.
Furthermore, many controllers are designed to output control signals to various dynamical components of a system based on a control model and sensor feedback from the system. Many systems are designed to exhibit a predetermined behavior or mode of operation, and the control components of the system are therefore designed, by traditional design and optimization techniques, to ensure that the predetermined system behavior transpires under normal operational conditions. A more difficult control problem involves design and implementation of controllers that can produce desired system operational behaviors that are specified following controller design and implementation. Theoreticians, researchers, and developers of many different types of controllers and automated systems continue to seek approaches to controller design to produce controllers with the flexibility and intelligence to control systems to produce a wide variety of different operational behaviors, including operational behaviors specified after controller design and manufacture.
Although certain control systems in existence before those described below have been used in efforts to improve energy-efficiency, these prior control systems may depend heavily on user feedback, and such user feedback could be energy-inefficient. For example, many users may select temperature setpoints for an HVAC system based primarily on comfort, rather than energy-efficiency. Yet such energy-inefficient feedback could cause a control system to inefficiently control the HVAC system.